Some off-the-beaten uses of Python learned from reading libraries. | Continue reading
15 minutes a week to document your work, increase visibility, and earn trust. | Continue reading
Understanding and spotting patterns to use code and components as intended. | Continue reading
Mindset, 100-day plan, and balancing learning and taking action to earn trust. | Continue reading
Industry examples, exploration strategies, warm-starting, off-policy evaluation, and more. | Continue reading
What to consider for in terms of data, roadmap, role, manager, tooling, etc. | Continue reading
How to generate labels from scratch with semi, active, and weakly supervised learning. | Continue reading
Why this is the first rule, some baseline heuristics, and when to move on to machine learning. | Continue reading
Breaking it into offline vs. online environments, and candidate retrieval vs. ranking steps. | Continue reading
Breaking it into offline vs. online environments, and candidate retrieval vs. ranking steps. | Continue reading
A whirlwind tour of bandits, embedding+MLP, sequences, graph, and user embeddings. | Continue reading
Access, serving, integrity, convenience, autopilot; use what you need. | Continue reading
Stop procrastinating, go off the happy path, learn just-in-time, and get your hands dirty. | Continue reading
As our careers grow, how does the balance between writing & coding change? Hear from 4 tech leaders. | Continue reading
DNS server snafus leading to missing email and security issues. Also, limited free build minutes monthly. | Continue reading
Instead of | Continue reading
Can maintaining machine learning in production be easier? I go through some practical tips. | Continue reading
Why (and why not) be more end-to-end, how to, and Stitch Fix and Netflix's experience | Continue reading
How not to become an expert beginner and to progress through beginner, intermediate, and so on. | Continue reading
Why (and why not) be more end-to-end, how to, and Stitch Fix and Netflix's experience | Continue reading
Why (and why not) be more end-to-end, how to, and Stitch Fix and Netflix's experience | Continue reading
After this article, we'll have a workflow of tests and checks that run automatically with each git push. | Continue reading
Haste makes waste. Diving into a data science problem may not be the fastest route to getting it done. | Continue reading
Crocker's Law, cognitive dissonance, and how to receive (uncomfortable) feedback better. | Continue reading
Using a Zettelkasten helps you make connections between notes, improving learning and memory. | Continue reading
Can maintaining machine learning in production be easier? I go through some practical tips. | Continue reading
I thought deploying machine learning was hard. Then I had to maintain multiple systems in prod. | Continue reading
Should I join a start-up? Which offer should I accept? A simple metaphor to guide your decisions. | Continue reading